I. Field of the Invention
The present invention relates generally to computer modeling and management of systems and, more particularly, to computer simulation techniques with real-time system monitoring and optimization of electrical system performance.
II. Background of the Invention
Computer models of complex systems enable improved system design, development, and implementation through techniques for off-line simulation of the system operation. That is, system models can be created that computers can “operate” in a virtual environment to determine design parameters. All manner of systems can be modeled, designed, and operated in this way, including machinery, factories, electrical power and distribution systems, processing plants, devices, chemical processes, biological systems, and the like. Such simulation techniques have resulted in reduced development costs and superior operation.
Design and production processes have benefited greatly from such computer simulation techniques, and such techniques are relatively well developed, but such techniques have not been applied in real-time, e.g., for real-time operational monitoring and management. In addition, predictive failure analysis techniques do not generally use real-time data that reflect actual system operation. Greater efforts at real-time operational monitoring and management would provide more accurate and timely suggestions for operational decisions, and such techniques applied to failure analysis would provide improved predictions of system problems before they occur. With such improved techniques, operational costs could be greatly reduced.
For example, mission critical electrical systems, e.g., for data centers or nuclear power facilities, must be designed to ensure that power is always available. Thus, the systems must be as failure proof as possible, and many layers of redundancy must be designed in to ensure that there is always a backup in case of a failure. It will be understood that such systems are highly complex, a complexity made even greater as a result of the required redundancy. Computer design and modeling programs allow for the design of such systems by allowing a designer to model the system and simulate its operation. Thus, the designer can ensure that the system will operate as intended before the facility is constructed.
Once the facility is constructed, however, the design is typically only referred to when there is a failure. In other words, once there is failure, the system design is used to trace the failure and take corrective action; however, because such design are so complex, and there are many interdependencies, it can be extremely difficult and time consuming to track the failure and all its dependencies and then take corrective action that doesn't result in other system disturbances.
Moreover, changing or upgrading the system can similarly be time consuming and expensive, requiring an expert to model the potential change, e.g., using the design and modeling program. Unfortunately, system interdependencies can be difficult to simulate, making even minor changes risky.
For example, no reliable means exists for simulating electrical system performance under various “what if” scenarios (i.e., the electrical system performing under different equipment configurations and operational parameters). That is, there is currently no simulation or “blackboard” solution that exists for simulating real-time “what if” scenarios on an electrical power system for the purpose of analyzing their impact on the health, performance, and reliability of the electrical system. This analysis is critical to the design of electrical systems that can meet the power demands and maintain sufficient active and reactive power reserves to handle the ongoing changes in demand and disturbances to the system due to various contingencies.
Conventional systems use a rigid simulation model that does not take the actual power system alignment and aging effects into consideration when computing predicted electrical values. This makes it difficult if not impossible to reliably simulate the performance characteristics of an electrical system that is reflective of the real-time operational conditions.
A virtual system model that can align itself in real-time with the actual electrical system configuration, and ages with the facility is critical to obtaining predictions that are reflective of the ability of the electrical system to maintain operational reliability and stability when subjected to the “what if” scenarios under various contingency conditions. Without real-time synchronization and an aging ability, predictions become of little value as they are no longer reflective of the actual facility status and may lead to false conclusions.